With screening guidelines and financial coverage varying among health systems and insurers sometimes dramatically the model provides quantitative predictions of the mortality benefits, on average, in populations of women over the course of 40 years.
"We're not advocating any particular interval for mammography screening," says Sandra Lee, ScD, a biostatistician at Dana-Farber who developed the model along with Marvin Zelen, PhD, of Dana-Farber and the Harvard School of Public Health. "This is a preliminary tool to show policymakers the kind of information they can draw on to help them make decisions."
Lee will describe the development of the mathematical model, which made use of data from several past clinical trials of mammography screening and from cancer databases, in a presentation at the annual meeting of the American Association for the Advancement of Science on Sunday, Feb. 20, 8:30 am (Marriott Wardman Park Hotel, Lobby Level, Maryland Suite C). She also will present that data at a press briefing later that day at 2 pm (Marriott Wardman Park Hotel, Mezzanine Level).
The mathematical tool generates comparative information that's impossible to obtain in the real world, say the scientists, because clinical trials would require hundreds of thousands of volunteers following a variety of schedules over many years to demonstrate small mortality differences and would be prohibitively expensive. Moreover, adds Lee, such trials would be ethically questionable because of the need for unscreened control groups.
At present, American Cancer Society guidelines recommend that women age 40 and older have a screening mammogram every year and that they "should continue to do so for as long as they are in good
Contact: Richard Saltus
Dana-Farber Cancer Institute